Generative AI Engineer

Phaxis; Nashville (TN); On-site; USD 120,000 - 180,000; Full time

Job summary

Phaxis is seeking an AI/ML-focused engineer to design and develop AI-powered solutions using Python, ML, and large language models. The role includes building LLM-based applications, context engineering, and prompt workflows to enable analytics-driven decision making.

You will develop data pipelines with Python, SQL, dbt and cloud technologies, construct predictive models, and integrate AI with BI platforms for self-service insights.

Qualifications

• Experience designing and deploying AI-powered solutions using Python and ML.
• Ability to build LLM-based applications, prompts, and analytics features.
• Experience creating data pipelines with Python, SQL, dbt and cloud tech.

Responsibilities

• Design and develop AI-powered solutions with Python, ML, and LLMs.
• Build and integrate LLM applications, including context engineering and prompts.
• Develop data pipelines with Python, SQL, dbt, and cloud tech.
• Create predictive models using ML techniques like Random Forest, NLP, and time-series.
• Integrate AI with BI tools for self-service insights and automation.
• Process large datasets using AWS, Spark, and Python to uncover trends.
• Collaborate with stakeholders to translate requirements into scalable AI solutions.
• Evaluate and optimize models for accuracy, performance, and business impact.

Skills

Python

Machine Learning

Large Language Models

Data pipelines

SQL

dbt

Cloud platforms

Spark

AWS

Tools

dbt

Spark

AWS

SQL

Job description

• Design and develop AI-powered solutions using Python, machine learning, and large language model technologies to address business and operational needs.
• Build and integrate LLM-based applications, including context engineering, prompt workflows, and AI-assisted analytics capabilities.
• Develop data pipelines and transformation workflows using Python, SQL, dbt, and cloud-based technologies to prepare high-quality data for AI and analytics applications.
• Develop predictive models using machine learning techniques such as Random Forest, clustering, time-series forecasting, NLP, and recommendation algorithms.
• Integrate AI solutions with analytics platforms and business intelligence tools to enable self-service insights and automated decision-making.
• Process and analyze large-scale datasets using AWS services, Spark, and Python to identify trends, develop features, and support data-driven solutions.
• Partner with business, clinical, operations, and technical stakeholders to translate complex requirements into scalable AI and analytics solutions.
• Evaluate and optimize AI models and data workflows for accuracy, performance, scalability, and practical business impact.